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Feat: add 4 seq subcommands — protparam, align, convert, random
- seq/protparam.py — Protein physicochemical properties via Biopython's ProteinAnalysis: MW, pI, extinction coeff, instability, aliphatic index, GRAVY, aromaticity, secondary structure fractions, charge at pH - seq/align.py — Pairwise alignment via Biopython PairwiseAligner (C impl): global/local mode, customizable scoring, multi-top output, score-only mode - seq/convert.py — Format conversion via Bio.SeqIO.convert(): one-line wrapper for all Biopython-supported format interconversion - seq/random.py — Random DNA (controlled GC) / protein sequence generation with reproducible seeds Zero new dependencies — all use biopython + stdlib only. 25 new tests, all pass. Co-Authored-By: Claude <noreply@anthropic.com>
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docs/en/module-seq.md

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# jsrc seq
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Sequence manipulation is the most routine task in bioinformatics. `jsrc seq` covers extraction, renaming, translation, QC, k-mer profiling, Entrez fetching, restriction digestion, sequence complexity, and MSA entropy.
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Sequence manipulation is the most routine task in bioinformatics. `jsrc seq` covers extraction, renaming, translation, protein characterization, QC, k-mer profiling, Entrez fetching, restriction digestion, sequence complexity, MSA entropy, pairwise alignment, format conversion, and random sequence generation.
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Genome-level analysis features (such as ORF finding, CpG island prediction, promoter extraction, tandem repeats, codon usage, sliding-window analysis, etc.) have been moved to the [genome module](./module-genome.md).
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@@ -127,3 +127,45 @@ jsrc seq entropy -fa aligned.fa
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jsrc seq entropy -fa aligned.fa --summary
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jsrc seq entropy -fa aligned.fa --json
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```
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## protparam
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After translation comes protein characterization. Given a FASTA of protein sequences, this command reports the core physicochemical properties for each protein: molecular weight, isoelectric point (pI), extinction coefficient, instability index, aliphatic index, GRAVY (hydropathy), aromaticity, and secondary structure fractions (helix/turn/sheet). Optionally computes net charge at a given pH.
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Uses Biopython's `ProteinAnalysis` under the hood. No external tools needed.
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```bash
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jsrc seq protparam -fa proteins.fa
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jsrc seq protparam -fa proteins.fa --json
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jsrc seq protparam -fa proteins.fa --ph 7.4 # with net charge at pH 7.4
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```
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## align
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Pairwise sequence alignment without installing anything extra. Uses Biopython's `PairwiseAligner` (a C implementation, fast enough for most needs). Supports global and local alignment, customizable match/mismatch/gap scores, and multi-top output.
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Two ways to provide input: two separate FASTA files (`-fa1` + `-fa2`), or one FASTA with at least two sequences (`-fa`). Use `--score-only` for quick numeric comparisons.
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```bash
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jsrc seq align -fa1 seq1.fa -fa2 seq2.fa
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jsrc seq align -fa both.fa --mode local --top 3
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jsrc seq align -fa1 a.fa -fa2 b.fa --match 2 --mismatch -1 --gap-open -2 --score-only
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```
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## convert
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The simplest command in the toolbox — one call to `Bio.SeqIO.convert()`. Converts between any formats Biopython understands: FASTA, GenBank, EMBL, Swiss-Prot, and many more. No need to remember format-specific conversion tools.
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```bash
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jsrc seq convert -i genome.gbk --from genbank --to fasta -o genome.fa
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jsrc seq convert -i proteins.swiss --from swiss --to fasta -o proteins.fa
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```
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## random
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Generate synthetic sequences for testing, benchmarking, or simulation. Produces DNA (controllable GC content) or protein sequences with reproducible seeds. Output to FASTA file or stdout.
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```bash
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jsrc seq random -t dna -n 10 -l 1000 --gc 0.45 --seed 123 -o sim.fa
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jsrc seq random -t protein -n 5 -l 300 # to stdout
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```

docs/zh/module-seq.md

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# jsrc seq
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序列操作是日常最绕不开的事。`jsrc seq` 涵盖了提取、重命名、翻译、质控、k-mer 指纹、Entrez 下载、酶切模拟、序列复杂度和 MSA 信息熵这些常用功能
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序列操作是日常最绕不开的事。`jsrc seq` 涵盖了提取、重命名、翻译、蛋白理化分析、质控、k-mer 指纹、Entrez 下载、酶切模拟、序列复杂度、MSA 信息熵、双序列比对、格式转换和随机序列生成这些常用功能
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基因组级别的分析功能(如 ORF 查找、CpG 岛预测、启动子提取、串联重复、密码子使用、滑窗统计等)已迁移到 [genome 模块](./module-genome.md)
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jsrc seq entropy -fa aligned.fa --summary
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jsrc seq entropy -fa aligned.fa --json
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```
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## protparam
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翻译完蛋白之后,自然想知道它们的理化性质。给一个蛋白序列的 FASTA 文件,这个命令会输出每个蛋白的核心指标:分子量、等电点(pI)、消光系数、不稳定指数、脂肪族指数、GRAVY(亲水性)、芳香性、以及二级结构分数(螺旋/转角/折叠)。还可以指定 pH 值算净电荷。
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底层用的是 Biopython 的 `ProteinAnalysis`,不需要额外依赖。
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```bash
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jsrc seq protparam -fa proteins.fa
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jsrc seq protparam -fa proteins.fa --json
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jsrc seq protparam -fa proteins.fa --ph 7.4 # 算 pH 7.4 时的净电荷
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```
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## align
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无需额外安装任何东西就能做双序列比对。用的是 Biopython 的 `PairwiseAligner`(C 实现,大多数场景下速度够用)。支持全局和局部比对,可自定义匹配/错配/空位罚分,也可以输出多个最优比对结果。
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两种输入方式:两个独立的 FASTA 文件(`-fa1` + `-fa2`),或者一个包含至少两条序列的 FASTA(`-fa`)。`--score-only` 可以快速得到纯分值,方便批量比较。
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```bash
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jsrc seq align -fa1 seq1.fa -fa2 seq2.fa
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jsrc seq align -fa both.fa --mode local --top 3
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jsrc seq align -fa1 a.fa -fa2 b.fa --match 2 --mismatch -1 --gap-open -2 --score-only
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```
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## convert
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工具箱里最简单的命令——就一行 `Bio.SeqIO.convert()`。在 Biopython 支持的所有格式之间互转:FASTA、GenBank、EMBL、Swiss-Prot 等等。不用记每个格式专用的转换工具。
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```bash
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jsrc seq convert -i genome.gbk --from genbank --to fasta -o genome.fa
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jsrc seq convert -i proteins.swiss --from swiss --to fasta -o proteins.fa
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```
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## random
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生成模拟序列,用于测试、基准测试或模拟分析。DNA 模式可精确控制 GC 含量,也支持生成蛋白序列。种子可复现,输出可选写入文件或打印到标准输出。
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```bash
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jsrc seq random -t dna -n 10 -l 1000 --gc 0.45 --seed 123 -o sim.fa
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jsrc seq random -t protein -n 5 -l 300 # 输出到标准输出
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```

src/jsrc/seq/__init__.py

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"digest": ("jsrc.seq.digest", "Simulate restriction enzyme digestion"),
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"rename": ("jsrc.seq.rename", "Rename FASTA headers"),
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"translate": ("jsrc.seq.translate", "Translate CDS/DNA to protein"),
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"protparam": ("jsrc.seq.protparam", "Protein physicochemical properties"),
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"qc": ("jsrc.seq.qc", "Sequence quality statistics"),
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"kmer": ("jsrc.seq.kmer", "Count k-mer frequencies"),
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"primer": ("jsrc.seq.primer", "Primer Tm, GC, and hairpin analysis"),
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"complexity": ("jsrc.seq.complexity", "Sequence complexity metrics"),
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"entropy": ("jsrc.seq.entropy", "Per-column Shannon entropy of MSA"),
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"align": ("jsrc.seq.align", "Pairwise sequence alignment"),
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"convert": ("jsrc.seq.convert", "Convert between sequence file formats"),
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"random": ("jsrc.seq.random", "Generate random sequences"),
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}
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src/jsrc/seq/align.py

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import logging
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from argparse import Namespace
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from typing import Any
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from Bio import SeqIO
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from Bio.Align import PairwiseAligner
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from jsrc.core import ValidationError
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logger = logging.getLogger(__name__)
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def _first_seq(path: str) -> str:
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rec = next(SeqIO.parse(path, "fasta"), None)
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if rec is None:
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raise ValidationError(f"No sequence found in {path}")
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return str(rec.seq).upper().replace("U", "T")
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def cmd(args: Namespace) -> None:
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if args.fa1 and args.fa2:
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s1 = _first_seq(args.fa1)
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s2 = _first_seq(args.fa2)
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elif args.fa:
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records = list(SeqIO.parse(args.fa, "fasta"))
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if len(records) < 2:
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raise ValidationError(
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"Need 2 sequences in FASTA (or use -fa1/-fa2)"
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)
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s1 = str(records[0].seq).upper().replace("U", "T")
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s2 = str(records[1].seq).upper().replace("U", "T")
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else:
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raise ValidationError("Provide -fa1/-fa2 or -fa (with 2+ sequences)")
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if not s1 or not s2:
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raise ValidationError("Both sequences must be non-empty")
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aligner = PairwiseAligner()
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aligner.mode = args.mode
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if args.match is not None:
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aligner.match_score = args.match
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if args.mismatch is not None:
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aligner.mismatch_score = args.mismatch
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if args.gap_open is not None:
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aligner.open_gap_score = args.gap_open
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if args.gap_extend is not None:
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aligner.extend_gap_score = args.gap_extend
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score = aligner.score(s1, s2)
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logger.info(
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"Alignment mode=%s score=%.1f match=%.1f mismatch=%.1f gap_open=%.1f gap_extend=%.1f",
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args.mode,
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score,
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aligner.match_score,
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aligner.mismatch_score,
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aligner.open_gap_score,
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aligner.extend_gap_score,
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)
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if args.score_only:
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print(f"{score:.1f}")
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return
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alignments = sorted(aligner.align(s1, s2), key=lambda a: a.score, reverse=True)
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for i, aln in enumerate(alignments[: args.top]):
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if args.top > 1:
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print(f"# Alignment {i + 1} (score={aln.score:.1f})")
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prefix = s2[:50]
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print(aln.format()[:2000] if len(prefix) < 80 else aln.format())
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def register(subparsers: Any) -> None:
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p = subparsers.add_parser("align", help="Pairwise sequence alignment")
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group = p.add_mutually_exclusive_group(required=True)
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group.add_argument("-fa", help="FASTA file with 2+ sequences")
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group.add_argument("-fa1", help="First sequence FASTA")
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p.add_argument("-fa2", help="Second sequence FASTA (requires -fa1)")
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p.add_argument(
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"-a",
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"--mode",
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choices=["global", "local"],
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default="global",
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help="Alignment mode (default: global)",
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)
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p.add_argument("--match", type=float, default=None, help="Match score")
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p.add_argument("--mismatch", type=float, default=None, help="Mismatch score")
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p.add_argument("--gap-open", type=float, default=None, help="Open gap score")
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p.add_argument("--gap-extend", type=float, default=None, help="Extend gap score")
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p.add_argument(
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"--top",
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type=int,
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default=1,
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help="Number of top alignments to show (default: 1)",
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)
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p.add_argument(
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"--score-only",
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action="store_true",
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help="Print only the alignment score",
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)
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p.set_defaults(func=cmd)

src/jsrc/seq/convert.py

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import logging
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from argparse import Namespace
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from pathlib import Path
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from typing import Any
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from Bio import SeqIO
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from jsrc.core import ValidationError
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logger = logging.getLogger(__name__)
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def cmd(args: Namespace) -> None:
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in_path = Path(args.input)
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if not in_path.exists():
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raise ValidationError(f"Input file not found: {args.input}")
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out_path = Path(args.o)
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count = SeqIO.convert(str(in_path), args.from_fmt, str(out_path), args.to_fmt)
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logger.info(
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"Converted %d records from %s → %s: %s", count, args.from_fmt, args.to_fmt, out_path
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)
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def register(subparsers: Any) -> None:
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p = subparsers.add_parser("convert", help="Convert between sequence file formats")
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p.add_argument("-i", "--input", required=True, help="Input file")
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p.add_argument("--from", dest="from_fmt", required=True, help="Source format")
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p.add_argument("--to", dest="to_fmt", required=True, help="Target format")
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p.add_argument("-o", required=True, help="Output file")
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p.set_defaults(func=cmd)

src/jsrc/seq/protparam.py

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import json
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import logging
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from argparse import Namespace
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from typing import Any
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from Bio import SeqIO
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from Bio.SeqUtils.ProtParam import ProteinAnalysis
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from jsrc.core import DataFormatError
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logger = logging.getLogger(__name__)
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_AA_VOLUMES: dict[str, float] = {
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"A": 1.0, "R": 6.13, "N": 2.95, "D": 2.78, "C": 2.43,
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"Q": 3.95, "E": 3.78, "G": 0.0, "H": 4.66, "I": 4.0,
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"L": 4.0, "K": 4.77, "M": 4.43, "F": 5.89, "P": 2.72,
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"S": 1.6, "T": 2.6, "W": 8.08, "Y": 6.47, "V": 3.0,
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}
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def _aliphatic_index(seq: str) -> float:
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"""Aliphatic index per Ikai (1980)."""
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aa = seq.upper()
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total = len(aa)
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if total == 0:
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return 0.0
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a = aa.count("A")
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v = aa.count("V")
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ile = aa.count("I")
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leu = aa.count("L")
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return (a + 2.9 * v + 3.9 * (ile + leu)) / total * 100.0
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def cmd(args: Namespace) -> None:
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records = list(SeqIO.parse(args.fa, "fasta"))
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if not records:
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raise DataFormatError("No protein sequences found in FASTA")
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results = []
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for rec in records:
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seq = str(rec.seq).upper().replace("U", "T")
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clean = "".join(c for c in seq if c.isalpha())
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if not clean:
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continue
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pa = ProteinAnalysis(clean)
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try:
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mw = pa.molecular_weight()
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except Exception:
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mw = 0.0
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try:
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pi = pa.isoelectric_point()
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except Exception:
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pi = 0.0
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try:
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ec = pa.molar_extinction_coefficient()
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except Exception:
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ec = (0, 0)
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try:
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ii = pa.instability_index()
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except Exception:
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ii = 0.0
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try:
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ai = _aliphatic_index(clean)
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except Exception:
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ai = 0.0
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try:
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gv = pa.gravy()
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except Exception:
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gv = 0.0
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try:
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ar = pa.aromaticity()
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except Exception:
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ar = 0.0
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try:
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ss = pa.secondary_structure_fraction()
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except Exception:
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ss = (0.0, 0.0, 0.0)
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charge = pa.charge_at_pH(args.ph) if args.ph is not None else None
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entry: dict[str, Any] = {
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"id": rec.id,
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"length": len(clean),
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"molecular_weight": round(mw, 2),
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"isoelectric_point": round(pi, 2),
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"extinction_coefficient_reduced": round(ec[0], 2),
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"extinction_coefficient_oxidized": round(ec[1], 2),
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"instability_index": round(ii, 2),
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"aliphatic_index": round(ai, 2),
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"gravy": round(gv, 4),
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"aromaticity": round(ar, 4),
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"helix_fraction": round(ss[0], 4),
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"turn_fraction": round(ss[1], 4),
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"sheet_fraction": round(ss[2], 4),
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}
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if charge is not None:
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entry["charge_at_pH"] = round(charge, 4)
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results.append(entry)
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if args.json:
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print(json.dumps(results, ensure_ascii=False, indent=2))
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return
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header = (
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"id\tlength\tmw\tpI\tEC_red\tEC_ox\tinstability\taliphatic\t"
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"gravy\taromaticity\thelix\tturn\tsheet"
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)
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if args.ph is not None:
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header += "\tcharge"
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print(header)
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for r in results:
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row = (
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f"{r['id']}\t{r['length']}\t{r['molecular_weight']}\t"
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f"{r['isoelectric_point']}\t{r['extinction_coefficient_reduced']}\t"
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f"{r['extinction_coefficient_oxidized']}\t{r['instability_index']}\t"
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f"{r['aliphatic_index']}\t{r['gravy']}\t{r['aromaticity']}\t"
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f"{r['helix_fraction']}\t{r['turn_fraction']}\t{r['sheet_fraction']}"
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)
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if args.ph is not None:
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row += f"\t{r.get('charge_at_pH', '')}"
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print(row)
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logger.info("Analyzed %d protein sequences", len(results))
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def register(subparsers: Any) -> None:
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p = subparsers.add_parser(
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"protparam", help="Protein physicochemical properties"
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)
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p.add_argument("-fa", required=True, help="Protein FASTA file")
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p.add_argument("--json", action="store_true", help="Print JSON output")
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p.add_argument("--ph", type=float, default=None, help="pH for net charge")
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p.set_defaults(func=cmd)

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